Distribution free estimation of heteroskedastic binary response models using probit/logit criterion functions

DOI10.1016/j.jeconom.2012.08.002zbMath1443.62477OpenAlexW2099955008MaRDI QIDQ528130

Shakeeb Khan

Publication date: 12 May 2017

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: http://www.sciencedirect.com/science/article/pii/S0304407612001753

zbMATH Keywords

binary responseheteroskedasticitysieve estimationprobit/logit

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Applications of statistics to economics (62P20) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)

Related Items (10)

Informational content of special regressors in heteroskedastic binary response models ⋮ Best subset binary prediction ⋮ Constructing Flexible, Identifiable and Interpretable Statistical Models for Binary Data ⋮ Relaxing conditional independence in an endogenous binary response model ⋮ Sieve \(M\) inference on irregular parameters ⋮ Binary quantile regression with local polynomial smoothing ⋮ Sieve semiparametric two-step GMM under weak dependence ⋮ Semiparametric estimation of a class of generalized linear models without smoothing ⋮ SMOOTHED QUANTILE REGRESSION PROCESSES FOR BINARY RESPONSE MODELS ⋮ A practical guide to compact infinite dimensional parameter spaces

Uses Software

• Stata

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